Previous researchers in speech perception looked for invariant cues that uniquely specified the phonetic identity of a speech segment. Instead, researchers discovered multiple, context-dependent cues used by listeners in making phonetic judgements. The goal of this research is to investigate the mapping from these perceptually relevant, acoustic cues to linguistic units in stop consonant perception by comparing the performance of statistical and neural models to results from human psychophysical studies, which will be undertaken. Through this comparison, the research will create a functional model of stop consonant perception, determine how much of perception is dictated by these cues, provide insight into whether more complex representations are needed, and provide a basis for searching for other acoustic cues. The first stage will extend an initial list of known perceptually relevant acoustic cues by testing possible acoustic cues on human subjects to see if a given cue affects phonetic judgment. The second stage will compare human and model performance on synthetic speech stimuli, using the acoustic cues that were determined in the first stage, to determine if a more complex representation is needed, and which representation most closely emulates human perception. Finally, the performance of both humans and the previously-trained models will be evaluated on novel real speech tokens to determine how much of natural stop consonant perception can be accounted for based solely on these cues. In addition, the discrepancies will be used as an impetus for discovering more acoustic cues. This research will not only provide insight into speech perception and provide a model, but it could also be used to improve hearing aids by accentuating the relevant attributes.